这是我的第一个问题,所以请不要对我太严格。
我需要比较估计量的质量。我有以下数据和代码。我需要了解的是,了解更好估计的唯一方法是查看图形,还是有一种更精确的方法来查看图形。预先感谢!
WT<-c(75, 265, 225, 402, 35, 105, 411, 346, 159, 229, 62, 256, 431, 177, 56, 144, 354, 178, 386, 294)
hist(WT,breaks=10,freq=F)
h<-hist(WT,breaks=quantile(WT,seq(0,1,0.1)),main="WT distribution")
cumfreq2<-cumsum(h$counts)/length(WT)
plot(h$breaks,c(0,cumfreq2),"l",main="Distribution
function",xlab="WT",ylab="Probabilite")+
lines(h$breaks,punif(h$breaks,min(WT),max(WT)),col="red")
#Estimate the parameter of this law by the method of moments.
u<-mean(WT)
v<-sqrt(sum((WT-u)^2)/length(WT)) # ce n'est pas le sqrt(var?) sqrt(var(WT))
a<-u-sqrt(3)*v #pourquoi 3
b<-u+sqrt(3)*v
#Estimate this parameter by the maximum likelihood method.
teta2<-max(WT)
#Compare the quality of these estimators by cumulative frequency graph
plot(h$breaks,c(0,cumfreq2),"l",main="Distribution
function",xlab="WT",ylab="Probabilite")+
lines(h$breaks,punif(h$breaks,min=a,max=b),col="red")
uni<-function(x){
if (x<=0){
y<-0
}else if (x<teta2) {
y<-x/teta2
}else {
y<-1
}
return(y)
}
lines(h$breaks,uni(h$breaks),col="blue")